2157 results about "Semantic analytics" patented technology

The method, system, and computer program provides the capability to compute measurements of the similarity between portions of text based on semantic profiles of the text portions. A computer-implemented method of determining similarity between portions of text comprises generating a semantic profile for at least two portions of text, each semantic profile comprising a vector of values and computing a similarity metric representing a similarity between the at least two portions of text using the at least two generated semantic profiles. The semantic profile comprises a vector of information values.

A computer program method enables a user to find the most relevant documents by searching of distributed databases, i.e., the World Wide Web. The program employs the user's profile, based on the user's foci of interest, the user's query and a semantic analysis of the query and documents. In one embodiment, the retrieved documents are ranked according to relevancy based on the user's profile and query.

Systems and methods for collecting, processing, analyzing, and indexing large amounts of data in such a manner that queries can be formulated and exercised against the data in an expedient manner. Embodiments of the present invention provide for static or dynamic presentation of the indexed data based upon the queries. The data organization and access techniques applied in embodiments of the present invention are structured in a way that allows for a large variety of queries to be performed on the data without having to reorganize the data. Additionally, indexes and presentations of the data are continually updated and modified in virtually real-time.

A method, system and computer program product for assisting the authoring of electronic messages are disclosed. Operations performed according to an example embodiment may include:

• • accessing an electronic message stored in digital form in a computer memory;
  • inspecting the electronic message to identify intended recipients of the electronic message;
  • gathering and analyzing historical data stored in digital form in a computer memory
  • relating to a conversation history that links an author of the electronic message to the intended recipients;
  • performing semantic analysis on the electronic message to extract words and phrases representing recipient fitness information that is indicative of whether the electronic message is appropriate for the intended recipients;
  • generating a fitness result for the electronic message by comparing the recipient fitness information to the historical data and identifying inconsistencies; and
  • outputting the fitness result for viewing on an electronic display device associated with the author of the electronic message.

The invention discloses a query sentence analyzing method based on understanding of natural languages and a system thereof, and belongs to the technical field of information retrieval. The query sentence analyzing method comprises the following steps: (1) automatic segmenting, named entity identification and part-of-speech tagging of an input Chinese query sentence are implemented; (2) syntax structure of the segmented sentence is analyzed so as to obtain a syntax structural tree, and meaning of each word is determined according to the sentence after the part-of-speech tagging; (3) according to the syntax structure and the meaning of each word, semantic roles of predicates in the sentence are tagged; and (4) according to the analyzed result of the sentence from the levels of syntactics, syntax and semantics, keywords are expanded and the keywords that can reflect user information retrieval requirements are extracted. The query sentence analyzing system of the invention comprises a syntactic analyzing module, a syntax analyzing module, a semantic analyzing module and a keyword extracting module. The query sentence analyzing method and system can greatly improve the accuracy of query results and provide desired query results for users.

Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.

The invention discloses a system and method for constructing information-analysis-oriented knowledge maps. The system comprises a data acquisition module, a text extraction module, an entity recognition module, a semantic analysis module and an entity-relation extraction module, wherein the data acquisition module is used for carrying out cleaning and simple preprocessing on acquired data and outputting the data to the text extraction module; the text extraction module is used for carrying out data cleaning and preprocessing on structured and unstructured data and conveying clean data to the entity recognition module; the entity recognition module is used for segmenting words of a text, marking the word characteristics of the segmented words, then extracting terms and conveying extracted results to the semantic analysis module; the semantic analysis module is used for analyzing and extracting relation among bodies, generating a semantic metadata model by a body construction tool and outputting the semantic metadata model to the entity-relation extraction module; and the entity-relation extraction module is used for finally generating knowledge map language by extracting taxonomic relation and non-taxonomic relation. The system and method disclosed by the invention have the advantages that by combination of syntactic training and association rules, not only are external input and artificial intervention reduced, but also the entity relation can be continuously recognized.

A method and system for semantically analyzing unstructured data in a customer feedback is provided. The method includes extracting data related to customer feedback from one or more input sources. The method further includes assigning weights to the one or more input sources and extracting relevant text from the feedback data. Further, sentences are detected from the customer feedback and are annotated. Thereafter, relevant adjectives are determined and are associated with sentence types. A rating is calculated for each sentence of the relevant text and output is provided in a pre-determined format.

A method and associated system of cross-retail marketing based on analysis of multichannel clickstream data that comprises a client application capturing, aggregating, and analyzing multiple clickstreams of a user. These clickstreams may be captured from multiple unrelated or competing sales or distribution channels and from multiple electronic platforms. The analysis may use methods of artificial intelligence, text analytics, semantic analytics, or other analytical methods to infer characteristics of the user, of the user's online commercial behavior and other commercial activities, and of products or services that the user may be interested in purchasing. The output of this analysis is forwarded to other channels or platforms visited by the user in order to allow those other channels or platforms to perform targeted commercial marketing functions related to the user's prior activities. In preferred embodiments, this method may be require an active consent or other authorization from the user.

The invention relates to computer science, information-search and intelligent systems, and can be used in developing information-search and other information and intelligent systems that operate on the basis of Internet. The invention provides the possibility of automatic creation of knowledge by extraction of knowledge from textual documents in electronic form in different languages; intelligent processing of textual information and users' requests to extract knowledge in any foreign language. The claimed method provides a mechanism of self-learning in the form of a stochastically indexed system of artifical intelligence, providing automatic instruction of the system in rules of grammatical and semantic analysis. The method includes creating databases of stochastically indexed dictionaries, tables of indices of linguistic texts and knowledge bases of morphological analysis; performing morphological and syntactical analysis, and also stochastic indexing of textual documents in respect to a given theme from the search system in a given language, and creating knowledge base of syntactical analysis. Stochastically indexed textual documents pertaining to the given theme are subjected to semantic analysis, and knowledge bases of semantic analysis. A user's request is compiled and transformed, in the stochastically indexed form, into a plurality of new requests that are equivalent to the original request; and stochastically indexed fragments of textual documents that comprise all word combinations of the transformed request are selected. A stochastically indexed structure is generated from the selected documents and basing on said structure by means of logical conclusion a brief reply of the system is generated. Relevancy of the obtained brief reply is checked by generating an interrogative sentence based on said reply, and by comparing said sentence with the request. When the user's request is identical to the obtained interrogative sentence, the decision is made that the brief reply of the system is identical to the request, and the reply is submitted to the user.

A method of network merchandising incorporates contextual and personalized advertising with human input to deliver relevant retail offers to interested online consumers efficiently and intelligently. Catalog content from retailers is downloaded, semantically analyzed and merged. The merged content is filtered using machine- and human-generated specifications to produce a merchandisable universe of products (MUP). Marketers and publishers create and modify corner store ad units and specify product offers from the MUP to display in those units. Publishers deploy the ad units on their web pages. Compensation of publishers by retailers can use a pay-for-performance model. Users visit the publisher's pages, viewing the product offers in the rendered ad unit. Performance data related to context, history, network and geo-location, product attributes and product combinations is derived from server log files is used to dynamically optimize and refine product placement in real time, providing a highly personalized experience for the user.

The embodiment of the invention provides an intelligent question-answer implementing method and system. The method comprises receiving a question to be queried; performing semantic analysis on the question; according to the result of the semantic analysis, performing corresponding retrieval treatment on the question, wherein the retrieval treatment comprises retrieval treatment on the question by at least one of a semantic relation digging system, a text library retrieving system, a knowledge base retrieving system and a question-answer library retrieving system; feeding an answer back according to the result of the retrieval treatment. The intelligent question-answer implementing method effectively improve the accuracy of question answering.

Related free-text documents, a corpus, are used to empirically derive a semantic knowledge base through a method in which documents are segmented into unique sentences, and then used to define sentential propositions which are arranged in a knowledge hierarchy. The method takes compound natural language sentences and transforms them to simple sentences by a process that is a part of the invention. A knowledge editor enables a domain expert using the methods of the invention to map the sentences in the corpus to sentential proposition(s). The resulting knowledge base can be used to semantically analyze documents in data mining and decision support applications, and can assist word processors or speech recognition devices. The invention is illustrated in connection with radiology reports, but it has wide applicability.

A method for predicting a canonical form for an input text sequence includes predicting the canonical form with a neural network model. The model includes an encoder, which generates a first representation of the input text sequence based on a representation of n-grams in the text sequence and a second representation of the input text sequence generated by a first neural network. The model also includes a decoder which sequentially predicts terms of the canonical form based on the first and second representations and a predicted prefix of the canonical form. The canonical form can be used, for example, to query a knowledge base or to generate a next utterance in a discourse.

Method for processing data, in which a Petri net is encoded, written into a memory and read and excuted by at least one instance, wherein transitions of the Petri net read from at least one tape and/or write on at least one tape symbols or symbol strings, with the aid of at least one head. [FIG. 1]. In an alternative, data-processing, co-operating nets are composed, the composition result is encoded, written into a memory and read and executed from the memory by at least one instance. In doing this, components can have cryptological functions. The data-processing nets can receive and process second data from a cryptological function which is executed in a protected manner. The invention enables processing of data which prevents semantic analysis of laid-open, possibly few processing steps and which can produce a linkage of the processing steps with a hardware which is difficult to isolate.

The invention provides a method for automatically generating software test cases. The method comprises the following steps of: A. reading to-be-tested software, carrying out lexical analysis, syntax analysis and semantic analysis on a source program of the to-be-tested software and generating an abstract syntax tree and a control flow graph of the to-be-tested software; B. preprocessing the source program of the to-be-tested software by traversing the generated abstract syntax tree, identifying initial input-output variables and compressing the space of a definition domain of the initial input variables; and C. generating a path of program elements of the current to-be-tested software by traversing the control flow graph, carrying out assignment operation, implication operation and backtracking operation on the variables in the path, and generating the test cases. The invention also provides a system for automatically generating software test cases. The method and the system for automatically generating the software test cases can accurately and automatically generate the test cases according to the given program elements of the to-be-tested software and verify the generated test cases, thereby improving the accuracy, efficiency and automation degree of the test cases.

The invention discloses a full text retrieval system based on natural language understanding, comprising: a database server, an information receiving judging module, a natural language processing module, a retrieving module, an indexing module, an index database and a result set processing module. The system of the invention provides two resolution strategies, that is, word classification static with semantic analysis associated with automatic segmentation and expanding inquired word static according to Hownet rule for low intelligence situation of current search engine. The deployed system converts information retrieval from current key word-based layer to knowledge (or concept)-based layer; the invention is capable of using techniques such as word classification, synonym, concept search, phrase identification, etc. with understanding and processing ability to knowledge. The search engine is provided with intelligence and humanization of information service. The user is allowed using natural language for information retrieval. The invention is capable of adding user selection behavior in interactive operation mode, so as to provide more convenient, more precise search service.

The invention discloses a user intention recognition method and device. The method includes the steps that in the process that a first user and a second user conduct conversation through an instant messaging tool, a first conversation text sent to the second user by the first user is received; the target text content to be analyzed is determined according to the first conversation text; first behavior data of the operation behavior executed by the first user and related to the second user are obtained in a user behavior database associated with the instant messaging tool; semantic analysis is conducted on the target text content in combination with the first behavior data, and the user intention recognition result is determined. By means of the user intention recognition method and device, the real intension of users can be recognized more accurately.

A question answering system includes a question answering unit, an analysis unit, a tree structure generation unit, a feature extraction unit, an evaluation unit and a re-ranking unit. The question answering unit executes search processing based on an input question and acquires answer candidates to the question. The analysis unit executes syntactic analysis processing or syntactic and semantic analysis processing on a passage obtained as a result of the search processing. The tree structure generation unit generates a tree structure based on an analysis result. The feature extraction unit extracts a relation between a search word applied in the search processing and each acquired answer candidate as a feature corresponding to each answer candidate from the tree structure. The evaluation unit determines an evaluation value of each answer candidate based on the feature extracted. The re-ranking unit re-ranks the answer candidates based on the evaluation values.